Evidence-Based Cognitive Rehabilitation: Systematic Review of the Literature From 2009 Through 2014

Objective To conduct an updated, systematic review of the clinical literature, classify studies based on the strength of research design, and derive consensual, evidence-based clinical recommendations for cognitive rehabilitation of people with TBI or stroke. Data Sources Online Pubmed and print journal searches identified citations for 250 articles published from 2009 through 2014. Study Selection 186 articles were selected for inclusion after initial screening. 50 articles were initially excluded (24 healthy, pediatric or other neurologic diagnoses, 10 non-cognitive interventions, 13 descriptive protocols or studies, 3 non-treatment studies). 15 articles were excluded after complete review (1 other neurologic diagnosis, 2 non-treatment studies, 1 qualitative study, 4 descriptive papers, 7 secondary analyses). 121 studies were fully reviewed. Data Extraction Articles were reviewed by CRTF members according to specific criteria for study design and quality, and classified as providing Class I, Class II, or Class III evidence. Articles were assigned to 1 of 6 possible categories (based on interventions for attention, vision and neglect, language and communication skills, memory, executive function, or comprehensive-integrated interventions). Data Synthesis Of 121 studies, 41 were rated as Class I, 3 as Class Ia, 14 as Class II, and 63 as Class III. Recommendations were derived by CRTF consensus from the relative strengths of the evidence, based on the decision rules applied in prior reviews. Conclusions CRTF has now evaluated 491 papers (109 Class I or Ia, 68 Class II, and 314 Class III) and makes 29 recommendations for evidence-based practice of cognitive rehabilitation (9 Practice Standards, 9 Practice Guidelines and 11 Practice Options). Evidence supports Practice Standards for attention deficits after TBI or stroke; visual scanning for neglect after right hemisphere stroke; compensatory strategies for mild memory deficits; language deficits after left hemisphere stroke; social communication deficits after TBI; metacognitive strategy training for deficits in executive functioning; and comprehensive-holistic neuropsychological rehabilitation to reduce cognitive and functional disability after TBI or stroke

Human Wavelength Discrimination of Monochromatic Light Explained by Optimal Wavelength Decoding of Light of Unknown Intensity

We show that human ability to discriminate the wavelength of monochromatic light can be understood as maximum likelihood decoding of the cone absorptions, with a signal processing efficiency that is independent of the wavelength. This work is built on the framework of ideal observer analysis of visual discrimination used in many previous works. A distinctive aspect of our work is that we highlight a perceptual confound that observers should confuse a change in input light wavelength with a change in input intensity. Hence a simple ideal observer model which assumes that an observer has a full knowledge of input intensity should over-estimate human ability in discriminating wavelengths of two inputs of unequal intensity. This confound also makes it difficult to consistently measure human ability in wavelength discrimination by asking observers to distinguish two input colors while matching their brightness. We argue that the best experimental method for reliable measurement of discrimination thresholds is the one of Pokorny and Smith, in which observers only need to distinguish two inputs, regardless of whether they differ in hue or brightness. We mathematically formulate wavelength discrimination under this wavelength-intensity confound and show a good agreement between our theoretical prediction and the behavioral data. Our analysis explains why the discrimination threshold varies with the input wavelength, and shows how sensitively the threshold depends on the relative densities of the three types of cones in the retina (and in particular predict discriminations in dichromats). Our mathematical formulation and solution can be applied to general problems of sensory discrimination when there is a perceptual confound from other sensory feature dimensions